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DBMS > gStore vs. Hyprcubd vs. Kinetica vs. Spark SQL

System Properties Comparison gStore vs. Hyprcubd vs. Kinetica vs. Spark SQL

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Editorial information provided by DB-Engines
NamegStore  Xexclude from comparisonHyprcubd  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionA native Graph DBMS to store and maintain very large RDF datasets.Serverless Time Series DBMSFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteen.gstore.cnhyprcubd.com (offline)www.kinetica.comspark.apache.org/­sql
Technical documentationen.gstore.cn/­#/­enDocsdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHyprcubd, Inc.KineticaApache Software Foundation
Initial release201620122014
Current release1.2, November 20237.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSDcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC, C++Scala
Server operating systemsLinuxhostedLinuxLinux
OS X
Windows
Data schemeschema-free and OWL/RDFS-schema supportyesyesyes
Typing infopredefined data types such as float or dateyesyes infotime, int, uint, float, stringyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesnoyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsHTTP API
SPARQL 1.1
gRPC (https)JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnouser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonono
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlUsers, roles and permissions, Role-Based Access Control (RBAC) supportedtoken accessAccess rights for users and roles on table levelno

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More resources
gStoreHyprcubdKineticaSpark SQL
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